Muhammad Salman

I am currently working with an organization in Cloud Management of AWS at the role of DevOps Engineer. With my current knowledge and experience, I am planning to leverage this opportunity to exploit different aspects of this technological era and to prove my skills as a DevOps Engineer.

 

I have been working with Amazon Web Services in Big Data and DevOps domains since 2019. I have hands-on experience in the following services:

·        IAM Roles and Policies

·        EC2, S3, Lambda

·        ECS, Aurora/RDS, CloudFront

·        VPC, VPN, NAT, Subnets, SecurityGroups

·        CloudWatch, SNS, SQS

·        Cognito, SSM, API Gateways

·        Auto Scaling, Elastic Load Balancer, Route53, DNS

·        Code Pipeline, Code Commit, Code Build, Code Deploy

·        AWS OpsWorks for Chef Automate, AWS FSx, AWS Transfer for SFTP

I have in-depth knowledge and experience in writing Infrastructure as Code and provisioning it in AWS cloud using following DevOps tools

·        AWS CloudFormation

·        Terraform

I have taken the challenge of building automation pipelines for Continuous Integration and Continuous Delivery to deploy code artifacts from different code versioning tools e.g. Github, Bitbucket with following DevOps tools:

·        AWS CodePipeline

·        Octopus CI/CD

 

I have Ingested unstructured data sources by building docker images via AWS Code Pipeline and deployed to AWS cloud using the following services:

·        AWS ECR (Elastic Container Registry)

·        AWS ECS (Elastic Container Service)

 

Moreover, I have hands-on in containerization and orchestration of microservices application using

·        Docker

·        Kubernetes

 

I have Instituted shell scripting and python scripting for automation of processes. I am Instrumental in troubleshooting, debugging, and error handling. With strong analytical and problem skills, I have worked with international clients with diverse teams in the agile/scrum software development process. Production experience with large scale distributed systems.